Many microdevices, such as integrated circuits, have become so complex that these devices cannot be manually designed. For example, even a simple microprocessor may have millions and millions of transistors that cooperate to form the components of the microprocessor. As a result, electronic design automation tools have been created to assist circuit designers in design a circuit, and then analyzing the circuit design before it is manufactured.
Designing and fabricating microcircuit devices involve many steps during a ‘design flow’ process. These steps are highly dependent on the type of microcircuit, its complexity, the design team, and the fabricator or foundry that will manufacture the microcircuit from the design. Several steps are common to most design flows, however. First, a design specification is modeled logically, typically in a hardware design language (HDL). Once a logical design has been created, various logical analysis processes are performed on the design to verify its correctness. More particularly, software and hardware “tools” verify that the logical design will provide the desired functionality at various stages of the design flow by running software simulators and/or hardware emulators, and errors are corrected. For example, a designer may employ one or more functional logic verification processes to verify that, given a specified input, the devices in a logical design will perform in the desired manner and provide the appropriate output.
After the logical design is deemed satisfactory, it is converted into physical design data by synthesis software. This physical design data or “layout” design data will include geometric elements representing the image that will be written onto a mask used to fabricate the desired microcircuit device in a photolithographic process at a foundry. While these geometric elements may be of any shape, with conventional mask or reticle writing tools the geometric elements typically will be polygons or line edges used to form polygons. Thus, the layout design data usually includes polygon data describing the features of polygons in the design. It is very important that the physical design information accurately embody the design specification and logical design for proper operation of the device. Accordingly, after it has been created during a synthesis process, the physical design data is compared with the original logical design schematic in a process sometimes referred to as a “layout-versus-schematic” (LVS) verification process.
Once the correctness of the logical design has been verified, and geometric data corresponding to the logical design has been created in a layout design, the geometric data then may be analyzed. For example, because the physical design data is employed to create masks used at a foundry, the data must conform to the foundry's requirements. Each foundry specifies its own physical design parameters for compliance with their processes, equipment, and techniques. Accordingly, the design flow may include a process to verify that the design data complies with the specified parameters. During this process, the physical layout of the circuit design is compared with design rules in a process commonly referred to as a “design rule check” (DRC) process. In addition to rules specified by the foundry, the design rule check process may also check the physical layout of the circuit design against other design rules, such as those obtained from test chips, general knowledge in the industry, previous manufacturing experience, etc. Examples of electronic design automation “verification” tools that perform these types of electronic design, automation verification processes include the Calibre family of software tools available from Mentor Graphics Corporation of Wilsonville, Oreg.
After a designer has used one or more geometry analysis processes to verify that the physical layout of the circuit design is satisfactory, the designer may then perform one or more simulation processes to simulate the operation of a manufacturing process, in order to determine how the design will actually be realized by that particular manufacturing process. A simulation analysis process may additionally modify the design to address any problems identified by the simulation. For example, some design flows may employ one or more processes to simulate the image formed by the physical layout of the circuit design during a photolithographic process, and then modify the layout design to improve the resolution of the image that it will produce during a photolithography process.
These resolution enhancement techniques (RET) may include, for example, modifying the physical layout using optical proximity correction (OPC) or by the addition of sub-resolution assist features (SRAF). Other simulation analysis processes may include, for example, phase shift mask (PSM) simulation analysis processes, etch simulation analysis processes and planarization simulation analysis processes. Etch simulation analysis processes simulate the removal of materials during a chemical etching process, while planarization simulation processes simulate the polishing of the circuit's surface during a chemical-mechanical etching process. These simulation analysis processes may identify, for example, regions where an etch or polishing process will not leave a sufficiently planar surface. These simulation analysis processes may then modify the physical layout design to, e.g., include more geometric elements in those regions to increase their density.
Once a physical layout design has been finalized, the geometric elements in the design are formatted for use by a mask or reticle writing tool. Masks and reticles typically are made using tools that expose a blank reticle or mask substrate to an electron or laser beam (or to an array of electron beams or laser beams), but most mask writing tools are able to only “write” certain kinds of polygons, however, such as right triangles, or rectangles or other trapezoids. Moreover, the sizes of the polygons are limited physically by the maximum beam (or beam array) size available to the tool. Accordingly, the larger polygons in a physical layout design data will typically be “fractured” into the smaller, more basic polygons that can be written by the mask or reticle writing tool.
As electronic design automation verification tools continue to develop, greater sophistication is being demanded from these tools. For example, in addition to detecting obvious design flaws, many electronic design automation verification tools are now expected to identify those design objects in a design that have a significant likelihood of being improperly formed during the manufacturing process, determine the resultant impact on manufacturing yield that these design objects will create, and/or identify design changes that will allow the design objects to be more reliably manufactured during the manufacturing process. Thus, the conventional design-rule-check rules employed by electronic design automation verification tools are becoming more complex as they consider not only single design features, such as wire spacing or gate width, but the interactions of multiple geometric elements in different configurations. This type of electronic design automation verification tool is sometimes referred to as a “design-for-manufacturing” tool.
Early design-for-manufacturing processes focused on addressing only a few specific and well-understood sources of manufacturing yield losses. For example, these design-for-manufacturing processes might typically identify portions of a design where increasing feature dimensions above a design minimum, adding redundant vias, expanding via enclosures, or other specific design improvement techniques could be expected to lead to measurable improvements in manufacturability. As the number of identified yield loss causes has increased, however, so has the complexity of yield prediction, eventually giving rise to a relatively complex set of design rules. Another source of complexity is the need for advanced device characterization, where additional device parameters, such as silicon stress or effective gate dimensions, must be extracted to properly analyze the manufacturability of devices. To address these complexities, some design-rule-check and design-for-manufacturability tools are following the evolution of the optical proximity correction (OPC) electronic design automation tools, from rule-based processes to model-based processes.
Some models are well-established, such as many of the optical models used by optical proximity correction (OPC) electronic design automation tools. Other manufacturing models, however, such as chemical-mechanical polishing (CMP) or strained silicon models, are still being actively developed and refined. Yet other manufacturing models, such as many yield assessment models, may be in the experimental or prototype stage. This diversity in models creates unique challenges for using model-based verification tools. The wide variety of desirable models makes it unlikely that a single verification tool or even an integrated set of verification tools contains all of the necessary models. On the other hand, using a collection of disparate design verification tools for every aspect of a design and manufacturing analysis that may require modeling makes design flow integration much more difficult. Further, some models may be very specific to a particular design methodology or manufacturing process, or contain sensitive proprietary information, preventing a designer from using commercially available verification tools.